import numpy as np
import pandas as pd
import os
import sys
import pickle
from joblib import dump, load
import yaml
import statsmodels.api as sm
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestRegressor
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import RandomizedSearchCV
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
from sklearn.linear_model import LinearRegression as reg
import pdb
from pprint import pprint
from statistics import mean
import random
random.seed(50)
import math
import argparse

sys.path.insert(1,'/REDACTED/fairness/code/rf/scripts/rf')
import tune_utils_alt_outcome as tu
from gpd_test_alt_outcome import *

###############################################
#### Hyperparameter Tuning
###############################################


sys.path.insert(1,'/REDACTED/fairness/code/rf/scripts/rf')
import tune_utils_alt_outcome as tu

tu.tune_model(train_fold=1, 
                 eitc=True,
                 dep_database=True,
                 datapath='/REDACTED/fairness/code/rf/data/',
                 model_type= 'reg',
                 threshold=None,
		 rs=50,
                 ts=0.25, ## test size
                 cvs=5,
                 njs=10,
		 outcome = 'ref_cred_amt_dif_pv')